Data Science Solutions with Python: fast and scalable models using Keras, PySpark MLlib, H2O, XGBoost, and Scikit-Learn
Saved in:
| Main Author: | |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Berkeley, CA
Apress
[2022]
|
| Subjects: | |
| Online Access: | FAB01 FAW01 FHA01 FHD01 FHI01 FHM01 FHN01 FHO01 FHR01 FKE01 FLA01 FWS01 FWS02 HTW01 UBR01 UBW01 UBY01 Volltext |
| Physical Description: | 1 Online-Ressource (XVI, 119 Seiten) |
| ISBN: | 9781484277621 |
| DOI: | 10.1007/978-1-4842-7762-1 |
Staff View
MARC
| LEADER | 00000nmm a2200000zc 4500 | ||
|---|---|---|---|
| 001 | BV047832142 | ||
| 003 | DE-604 | ||
| 005 | 20231206 | ||
| 007 | cr|uuu---uuuuu | ||
| 008 | 220211s2022 |||| o||u| ||||||eng d | ||
| 020 | |a 9781484277621 |c Online |9 978-1-4842-7762-1 | ||
| 024 | 7 | |a 10.1007/978-1-4842-7762-1 |2 doi | |
| 035 | |a (ZDB-2-CWD)9781484277621 | ||
| 035 | |a (OCoLC)1298746394 | ||
| 035 | |a (DE-599)BVBBV047832142 | ||
| 040 | |a DE-604 |b ger |e rda | ||
| 041 | 0 | |a eng | |
| 049 | |a DE-355 |a DE-860 |a DE-1046 |a DE-1043 |a DE-Aug4 |a DE-898 |a DE-188 |a DE-523 |a DE-859 |a DE-863 |a DE-1050 |a DE-20 |a DE-1051 |a DE-862 |a DE-92 |a DE-573 |a DE-M347 |a DE-706 |a DE-83 | ||
| 082 | 0 | |a 005.7 |2 23 | |
| 082 | 0 | |a 001.422 |2 23 | |
| 100 | 1 | |a Nokeri, Tshepo Chris |e Verfasser |0 (DE-588)1232349984 |4 aut | |
| 245 | 1 | 0 | |a Data Science Solutions with Python |b fast and scalable models using Keras, PySpark MLlib, H2O, XGBoost, and Scikit-Learn |c Tshepo Chris Nokeri |
| 264 | 1 | |a Berkeley, CA |b Apress |c [2022] | |
| 264 | 4 | |c © 2022 | |
| 300 | |a 1 Online-Ressource (XVI, 119 Seiten) | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b c |2 rdamedia | ||
| 338 | |b cr |2 rdacarrier | ||
| 650 | 4 | |a Data Analysis and Big Data | |
| 650 | 4 | |a Machine Learning | |
| 650 | 4 | |a Artificial Intelligence | |
| 650 | 4 | |a Python | |
| 650 | 4 | |a Quantitative research | |
| 650 | 4 | |a Machine learning | |
| 650 | 4 | |a Artificial intelligence | |
| 650 | 4 | |a Python (Computer program language) | |
| 776 | 0 | 8 | |i Erscheint auch als |n Druck-Ausgabe |z 978-1-4842-7761-4 |
| 776 | 0 | 8 | |i Erscheint auch als |n Druck-Ausgabe |z 978-1-4842-7763-8 |
| 856 | 4 | 0 | |u https://doi.org/10.1007/978-1-4842-7762-1 |x Verlag |z URL des Erstveröffentlichers |3 Volltext |
| 912 | |a ZDB-2-CWD | ||
| 940 | 1 | |q ZDB-2-CWD_2022 | |
| 999 | |a oai:aleph.bib-bvb.de:BVB01-033215376 | ||
| 966 | e | |u https://doi.org/10.1007/978-1-4842-7762-1 |l FAB01 |p ZDB-2-CWD |x Verlag |3 Volltext | |
| 966 | e | |u https://doi.org/10.1007/978-1-4842-7762-1 |l FAW01 |p ZDB-2-CWD |x Verlag |3 Volltext | |
| 966 | e | |u https://doi.org/10.1007/978-1-4842-7762-1 |l FHA01 |p ZDB-2-CWD |x Verlag |3 Volltext | |
| 966 | e | |u https://doi.org/10.1007/978-1-4842-7762-1 |l FHD01 |p ZDB-2-CWD |x Verlag |3 Volltext | |
| 966 | e | |u https://doi.org/10.1007/978-1-4842-7762-1 |l FHI01 |p ZDB-2-CWD |x Verlag |3 Volltext | |
| 966 | e | |u https://doi.org/10.1007/978-1-4842-7762-1 |l FHM01 |p ZDB-2-CWD |x Verlag |3 Volltext | |
| 966 | e | |u https://doi.org/10.1007/978-1-4842-7762-1 |l FHN01 |p ZDB-2-CWD |x Verlag |3 Volltext | |
| 966 | e | |u https://doi.org/10.1007/978-1-4842-7762-1 |l FHO01 |p ZDB-2-CWD |x Verlag |3 Volltext | |
| 966 | e | |u https://doi.org/10.1007/978-1-4842-7762-1 |l FHR01 |p ZDB-2-CWD |x Verlag |3 Volltext | |
| 966 | e | |u https://doi.org/10.1007/978-1-4842-7762-1 |l FKE01 |p ZDB-2-CWD |x Verlag |3 Volltext | |
| 966 | e | |u https://doi.org/10.1007/978-1-4842-7762-1 |l FLA01 |p ZDB-2-CWD |x Verlag |3 Volltext | |
| 966 | e | |u https://doi.org/10.1007/978-1-4842-7762-1 |l FWS01 |p ZDB-2-CWD |x Verlag |3 Volltext | |
| 966 | e | |u https://doi.org/10.1007/978-1-4842-7762-1 |l FWS02 |p ZDB-2-CWD |x Verlag |3 Volltext | |
| 966 | e | |u https://doi.org/10.1007/978-1-4842-7762-1 |l HTW01 |p ZDB-2-CWD |x Verlag |3 Volltext | |
| 966 | e | |u https://doi.org/10.1007/978-1-4842-7762-1 |l UBR01 |p ZDB-2-CWD |x Verlag |3 Volltext | |
| 966 | e | |u https://doi.org/10.1007/978-1-4842-7762-1 |l UBW01 |p ZDB-2-CWD |x Verlag |3 Volltext | |
| 966 | e | |u https://doi.org/10.1007/978-1-4842-7762-1 |l UBY01 |p ZDB-2-CWD |x Verlag |3 Volltext | |
Record in the Search Index
| DE-BY-FWS_katkey | 964805 |
|---|---|
| _version_ | 1824555167018647552 |
| adam_txt | |
| any_adam_object | |
| any_adam_object_boolean | |
| author | Nokeri, Tshepo Chris |
| author_GND | (DE-588)1232349984 |
| author_facet | Nokeri, Tshepo Chris |
| author_role | aut |
| author_sort | Nokeri, Tshepo Chris |
| author_variant | t c n tc tcn |
| building | Verbundindex |
| bvnumber | BV047832142 |
| collection | ZDB-2-CWD |
| ctrlnum | (ZDB-2-CWD)9781484277621 (OCoLC)1298746394 (DE-599)BVBBV047832142 |
| dewey-full | 005.7 001.422 |
| dewey-hundreds | 000 - Computer science, information, general works |
| dewey-ones | 005 - Computer programming, programs, data, security 001 - Knowledge |
| dewey-raw | 005.7 001.422 |
| dewey-search | 005.7 001.422 |
| dewey-sort | 15.7 |
| dewey-tens | 000 - Computer science, information, general works |
| discipline | Allgemeines Informatik |
| discipline_str_mv | Allgemeines Informatik |
| doi_str_mv | 10.1007/978-1-4842-7762-1 |
| format | Electronic eBook |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>03370nmm a2200673zc 4500</leader><controlfield tag="001">BV047832142</controlfield><controlfield tag="003">DE-604</controlfield><controlfield tag="005">20231206 </controlfield><controlfield tag="007">cr|uuu---uuuuu</controlfield><controlfield tag="008">220211s2022 |||| o||u| ||||||eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9781484277621</subfield><subfield code="c">Online</subfield><subfield code="9">978-1-4842-7762-1</subfield></datafield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/978-1-4842-7762-1</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(ZDB-2-CWD)9781484277621</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)1298746394</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)BVBBV047832142</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-604</subfield><subfield code="b">ger</subfield><subfield code="e">rda</subfield></datafield><datafield tag="041" ind1="0" ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-355</subfield><subfield code="a">DE-860</subfield><subfield code="a">DE-1046</subfield><subfield code="a">DE-1043</subfield><subfield code="a">DE-Aug4</subfield><subfield code="a">DE-898</subfield><subfield code="a">DE-188</subfield><subfield code="a">DE-523</subfield><subfield code="a">DE-859</subfield><subfield code="a">DE-863</subfield><subfield code="a">DE-1050</subfield><subfield code="a">DE-20</subfield><subfield code="a">DE-1051</subfield><subfield code="a">DE-862</subfield><subfield code="a">DE-92</subfield><subfield code="a">DE-573</subfield><subfield code="a">DE-M347</subfield><subfield code="a">DE-706</subfield><subfield code="a">DE-83</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">005.7</subfield><subfield code="2">23</subfield></datafield><datafield tag="082" ind1="0" ind2=" "><subfield code="a">001.422</subfield><subfield code="2">23</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Nokeri, Tshepo Chris</subfield><subfield code="e">Verfasser</subfield><subfield code="0">(DE-588)1232349984</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Data Science Solutions with Python</subfield><subfield code="b">fast and scalable models using Keras, PySpark MLlib, H2O, XGBoost, and Scikit-Learn</subfield><subfield code="c">Tshepo Chris Nokeri</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Berkeley, CA</subfield><subfield code="b">Apress</subfield><subfield code="c">[2022]</subfield></datafield><datafield tag="264" ind1=" " ind2="4"><subfield code="c">© 2022</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 Online-Ressource (XVI, 119 Seiten)</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Data Analysis and Big Data</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Machine Learning</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Artificial Intelligence</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Python</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Quantitative research</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Machine learning</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Artificial intelligence</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Python (Computer program language)</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Erscheint auch als</subfield><subfield code="n">Druck-Ausgabe</subfield><subfield code="z">978-1-4842-7761-4</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Erscheint auch als</subfield><subfield code="n">Druck-Ausgabe</subfield><subfield code="z">978-1-4842-7763-8</subfield></datafield><datafield tag="856" ind1="4" ind2="0"><subfield code="u">https://doi.org/10.1007/978-1-4842-7762-1</subfield><subfield code="x">Verlag</subfield><subfield code="z">URL des Erstveröffentlichers</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-2-CWD</subfield></datafield><datafield tag="940" ind1="1" ind2=" "><subfield code="q">ZDB-2-CWD_2022</subfield></datafield><datafield tag="999" ind1=" " ind2=" "><subfield code="a">oai:aleph.bib-bvb.de:BVB01-033215376</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1007/978-1-4842-7762-1</subfield><subfield code="l">FAB01</subfield><subfield code="p">ZDB-2-CWD</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1007/978-1-4842-7762-1</subfield><subfield code="l">FAW01</subfield><subfield code="p">ZDB-2-CWD</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1007/978-1-4842-7762-1</subfield><subfield code="l">FHA01</subfield><subfield code="p">ZDB-2-CWD</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1007/978-1-4842-7762-1</subfield><subfield code="l">FHD01</subfield><subfield code="p">ZDB-2-CWD</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1007/978-1-4842-7762-1</subfield><subfield code="l">FHI01</subfield><subfield code="p">ZDB-2-CWD</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1007/978-1-4842-7762-1</subfield><subfield code="l">FHM01</subfield><subfield code="p">ZDB-2-CWD</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1007/978-1-4842-7762-1</subfield><subfield code="l">FHN01</subfield><subfield code="p">ZDB-2-CWD</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1007/978-1-4842-7762-1</subfield><subfield code="l">FHO01</subfield><subfield code="p">ZDB-2-CWD</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1007/978-1-4842-7762-1</subfield><subfield code="l">FHR01</subfield><subfield code="p">ZDB-2-CWD</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1007/978-1-4842-7762-1</subfield><subfield code="l">FKE01</subfield><subfield code="p">ZDB-2-CWD</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1007/978-1-4842-7762-1</subfield><subfield code="l">FLA01</subfield><subfield code="p">ZDB-2-CWD</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1007/978-1-4842-7762-1</subfield><subfield code="l">FWS01</subfield><subfield code="p">ZDB-2-CWD</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1007/978-1-4842-7762-1</subfield><subfield code="l">FWS02</subfield><subfield code="p">ZDB-2-CWD</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1007/978-1-4842-7762-1</subfield><subfield code="l">HTW01</subfield><subfield code="p">ZDB-2-CWD</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1007/978-1-4842-7762-1</subfield><subfield code="l">UBR01</subfield><subfield code="p">ZDB-2-CWD</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1007/978-1-4842-7762-1</subfield><subfield code="l">UBW01</subfield><subfield code="p">ZDB-2-CWD</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="e" ind2=" "><subfield code="u">https://doi.org/10.1007/978-1-4842-7762-1</subfield><subfield code="l">UBY01</subfield><subfield code="p">ZDB-2-CWD</subfield><subfield code="x">Verlag</subfield><subfield code="3">Volltext</subfield></datafield></record></collection> |
| id | DE-604.BV047832142 |
| illustrated | Not Illustrated |
| index_date | 2024-07-03T19:09:28Z |
| indexdate | 2025-02-20T07:03:21Z |
| institution | BVB |
| isbn | 9781484277621 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-033215376 |
| oclc_num | 1298746394 |
| open_access_boolean | |
| owner | DE-355 DE-BY-UBR DE-860 DE-1046 DE-1043 DE-Aug4 DE-898 DE-BY-UBR DE-188 DE-523 DE-859 DE-863 DE-BY-FWS DE-1050 DE-20 DE-1051 DE-862 DE-BY-FWS DE-92 DE-573 DE-M347 DE-706 DE-83 |
| owner_facet | DE-355 DE-BY-UBR DE-860 DE-1046 DE-1043 DE-Aug4 DE-898 DE-BY-UBR DE-188 DE-523 DE-859 DE-863 DE-BY-FWS DE-1050 DE-20 DE-1051 DE-862 DE-BY-FWS DE-92 DE-573 DE-M347 DE-706 DE-83 |
| physical | 1 Online-Ressource (XVI, 119 Seiten) |
| psigel | ZDB-2-CWD ZDB-2-CWD_2022 |
| publishDate | 2022 |
| publishDateSearch | 2022 |
| publishDateSort | 2022 |
| publisher | Apress |
| record_format | marc |
| spellingShingle | Nokeri, Tshepo Chris Data Science Solutions with Python fast and scalable models using Keras, PySpark MLlib, H2O, XGBoost, and Scikit-Learn Data Analysis and Big Data Machine Learning Artificial Intelligence Python Quantitative research Machine learning Artificial intelligence Python (Computer program language) |
| title | Data Science Solutions with Python fast and scalable models using Keras, PySpark MLlib, H2O, XGBoost, and Scikit-Learn |
| title_auth | Data Science Solutions with Python fast and scalable models using Keras, PySpark MLlib, H2O, XGBoost, and Scikit-Learn |
| title_exact_search | Data Science Solutions with Python fast and scalable models using Keras, PySpark MLlib, H2O, XGBoost, and Scikit-Learn |
| title_exact_search_txtP | Data Science Solutions with Python fast and scalable models using Keras, PySpark MLlib, H2O, XGBoost, and Scikit-Learn |
| title_full | Data Science Solutions with Python fast and scalable models using Keras, PySpark MLlib, H2O, XGBoost, and Scikit-Learn Tshepo Chris Nokeri |
| title_fullStr | Data Science Solutions with Python fast and scalable models using Keras, PySpark MLlib, H2O, XGBoost, and Scikit-Learn Tshepo Chris Nokeri |
| title_full_unstemmed | Data Science Solutions with Python fast and scalable models using Keras, PySpark MLlib, H2O, XGBoost, and Scikit-Learn Tshepo Chris Nokeri |
| title_short | Data Science Solutions with Python |
| title_sort | data science solutions with python fast and scalable models using keras pyspark mllib h2o xgboost and scikit learn |
| title_sub | fast and scalable models using Keras, PySpark MLlib, H2O, XGBoost, and Scikit-Learn |
| topic | Data Analysis and Big Data Machine Learning Artificial Intelligence Python Quantitative research Machine learning Artificial intelligence Python (Computer program language) |
| topic_facet | Data Analysis and Big Data Machine Learning Artificial Intelligence Python Quantitative research Machine learning Artificial intelligence Python (Computer program language) |
| url | https://doi.org/10.1007/978-1-4842-7762-1 |
| work_keys_str_mv | AT nokeritshepochris datasciencesolutionswithpythonfastandscalablemodelsusingkeraspysparkmllibh2oxgboostandscikitlearn |